Scheduling Scientific Workflow on Cloud Using Meta-Heuristic Static Scheduling Algorithm

Abstract

Workflow has reduced the complexity of scientific applications. Other than Grid and Cluster, Cloud Computing is an ideal platform for an efficient workflow deployment. But due to its dynamic variation in VMs, many challenges come across it. Quality of Service (QoS) in terms of cost and execution time is a key issue in workflow scheduling. In this paper, the authors have proposed a scheduler that is inspired by PSO (particle swarm optimization) and works on a given deadline neglecting its constraint. The technique used is the meta-heuristic approach and results have been simulated inCloud Sim and experimental results show better performance of the proposed method as compared to other state -of-artalgorithms.